A new method using the dynamic mode decomposition algorithm has been developed to analyze hyperspectral images more efficiently. This method breaks down the images into spatial dynamic modes and spectral patterns, making it easier to process large amounts of data. By applying this approach to real hyperspectral images, researchers found that it can represent the images with a simpler model in the spectral dimension. This means that the method could be a valuable tool for reducing the complexity of hyperspectral image analysis.